Practical Deep Learning at Scale with MLflow

Table of Contents

Preface

Section 1 - Deep Learning Challenges and MLflow Prime

Chapter 1: Deep Learning Life Cycle and MLOps Challenges

Technical requirements

Understanding the DL life cycle and MLOps challenges

Implementing a basic DL sentiment classifier

Understanding DL's full life cycle development

Understanding MLOps challenges

Understanding DL data challenges

Understanding DL model challenges

Understanding DL code challenges

Understanding DL explainability challenges

Summary

Further reading

Chapter 2: Getting Started with MLflow for Deep Learning

Technical requirements

Setting up MLflow

Setting up MLflow locally using miniconda

Setting up MLflow to interact with a remote MLflow server

Implementing our first DL experiment with MLflow ...